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Understanding the brittle fracture behavior of rock is crucial for engineering and Earth science. In this paper, based on acoustic emission (AE) and laser Doppler vibration (LDV) monitoring technology, the staged damage behaviors of rock-like materials with different brittleness degrees under uniaxial compression are studied via multiple parameters. The results show that the brittleness degree determines the fracture mode. As the specimen's brittleness degree increases, the tensile failure increases and shear failure decreases. AE activity is enhanced at the crack damage point. With an increasing specimen brittleness degree, different instability precursor information is shown during the unstable crack growth stage: the AE b value changes from the fluctuating to continuously decreasing state, and the natural frequency changes from the stable fluctuation to upward fluctuation state. The AE b value near the stress drop is the smallest, and it decreases with an increasing brittleness degree. The natural frequency reduction indicates the rock-like fracture. The natural frequency is a symbolic index that reflects staged damage characteristics and predicts the amount of energy released by brittle failure. These findings provide guidelines for rock stability monitoring and provide support for better responses to stability evaluations of rock slopes, rock collapses, and tunnel surrounding rock in engineering. [ABSTRACT FROM AUTHOR]

Rice black-streaked dwarf virus (RBSDV) is the main pathogen causing maize rough dwarf disease (MRDD) in China. Typical enation symptoms along the abaxial leaf veins prevail in RBSDV-infected maize inbred line B73 (susceptible to RBSDV), but not in X178 (resistant to RBSDV). Observation of the microstructures of epidermal cells and cross section of enations from RBSDV-infected maize leaves found that the increase of epidermal cell and phloem cell numbers is associated with enation formation. To identify proteins associated with enation formation and candidate proteins against RBSDV infection, comparative proteomics between B73 and X178 plants were conducted using isobaric tags for relative and absolute quantitation (iTRAQ) with leaf samples at the enation forming stage. The proteomics data showed that 260 and 316 differentially expressed proteins (DEPs) were identified in B73 and X178, respectively. We found that the majority of DEPs are located in the chloroplast and cytoplasm. Moreover, RBSDV infection resulted in dramatic changes of DEPs enriched by the metabolic process, response to stress and the biosynthetic process. Strikingly, a cell number regulator 10 was significantly down-regulated in RBSDV-infected B73 plants. Altogether, these data will provide value information for future studies to analyze molecular events during both enation formation and resistance mechanism to RBSDV infection. [ABSTRACT FROM AUTHOR]

Expression and purification of β-galactosidases derived from Bifidobacterium provide a new resource for efficient lactose hydrolysis and lactose intolerance alleviation. Here, we cloned and expressed two β-galactosidases derived from Bifidobacterium. The optimal pH for BLGLB1 was 5.5, and the optimal temperature was 45 °C, at which the enzyme activity of BLGLB1 was higher than that of commercial enzyme E (300 ± 3.6 U/mg) under its optimal conditions, reaching 2200 ± 15 U/mg. The optimal pH and temperature for BPGLB1 were 6.0 and 45 °C, respectively, and the enzyme activity (0.58 ± 0.03 U/mg) under optimum conditions was significantly lower than that of BLGLB1. The structures of the two β-galactosidase were similar, with all known key sites conserved. When o-nitrophenyl-β-D-galactoside (oNPG) was used as an enzyme reaction substrate, the maximum reaction velocity (Vmax) for BLGLB1 and BPGLB1 was 3700 ± 100 U/mg and 1.1 ± 0.1 U/mg, respectively. The kinetic constant (Km) of BLGLB1 and BPGLB1 was 1.9 ± 0.1 and 1.3 ± 0.3 mmol/L, respectively. The respective catalytic constant (kcat) of BLGLB1 and BPGLB1 was 1700 ± 40 s−1 and 0.5 ± 0.02 s−1, respectively; the respective kcat/Km value of BLGLB1 and BPGLB1 was 870 L/(mmol∙s) and 0.36 L/(mmol∙s), respectively. The Km, kcat and Vmax values of BLGLB1 were superior to those of earlier reported β-galactosidase derived from Bifidobacterium. Overall, BLGLB1 has potential application in the food industry. [ABSTRACT FROM AUTHOR]

The abundant and widespread unicellular cyanobacteria Synechococcus plays an important role in contributing to global phytoplankton primary production. In the present study, two novel cyanomyoviruses, S-N03 and S-H34 that infected Synechococcus MW02, were isolated from the coastal waters of the Yellow Sea. S-N03 contained a 167,069-bp genome comprising double-stranded DNA with a G + C content of 50.1%, 247 potential open reading frames and 1 tRNA; S-H34 contained a 167,040-bp genome with a G + C content of 50.1%, 246 potential open reading frames and 5 tRNAs. These two cyanophages contain fewer auxiliary metabolic genes (AMGs) than other previously isolated cyanophages. S-H34 in particular, is currently the only known cyanomyovirus that does not contain any AMGs related to photosynthesis. The absence of such common AMGs in S-N03 and S-H34, their distinct evolutionary history and ecological features imply that the energy for phage production might be obtained from other sources rather than being strictly dependent on the maintenance of photochemical ATP under high light. Phylogenetic analysis showed that the two isolated cyanophages clustered together and had a close relationship with two other cyanophages of low AMG content. Comparative genomic analysis, habitats and hosts across 81 representative cyanomyovirus showed that cyanomyovirus with less AMGs content all belonged to Synechococcus phages isolated from eutrophic waters. The relatively small genome size and high G + C content may also relate to the lower AMG content, as suggested by the significant correlation between the number of AMGs and G + C%. Therefore, the lower content of AMG in S-N03 and S-H34 might be a result of viral evolution that was likely shaped by habitat, host, and their genomic context. The genomic content of AMGs in cyanophages may have adaptive significance and provide clues to their evolution. [ABSTRACT FROM AUTHOR]

Trap-controlled mechanoluminescent (ML) materials characterized by reproducible mechanoluminescence (ML) after irradiation recharging have shown attractive prospects in applications including stress distribution visualization, stress-driven light sources, and anti-counterfeiting. However, these materials generally suffer from the difficulty of achieving non-decaying ML when subjected to continuous mechanical stimulation. Herein, we develop a trap-controlled reproducible ML material, Li2MgGeO4:Mn2+, and report its short-term non-decaying ML behavior. Investigation of trap properties suggests that the unique non-decaying ML behavior should arise from the deep traps existing in Li2MgGeO4:Mn2+, which provide electron replenishment for shallow traps that release small numbers of electrons during short-term cyclic friction. Our results are expected to provide a reference for the ultimate achievement of long-term non-decaying ML in such materials. [ABSTRACT FROM AUTHOR]

In recent years, Hydro-pneumatic cycling compressed air energy storage (HC-CAES) has become an important topic in compressed air energy storage (CAES) technology research. In HC-CAES, air is compressed by liquid and driven by electrical equipment when energy is stored, and then, liquid is used to drive the water conservancy equipment to generate electricity. In this study, adaptive hydraulic potential energy transfer technology is proposed to solve a series of problems in the HC-CAES system, including the high fluctuation range of gas potential energy, poor operating stability, low efficiency, and so on. Therefore, fluctuating potential energy can be stably transferred through the variable area hydraulic devices, which can be controlled with an on–off valve. The structure and operation scheme of the adaptive hydraulic potential energy transfer device used in the HC-CAES system are explained in detail; the device can provide a stable water head range for the highly efficient operation of water conservancy equipment. Moreover, an optimal operation scheme was determined through simulation analysis; a physical experiment platform was built to verify the feasibility of the design and stability of system operation. [ABSTRACT FROM AUTHOR]

Airborne synthetic aperture radar (SAR) is susceptible to atmospheric disturbance and other factors that cause the position offset error of the antenna phase center and motion error. In close-range detection scenarios, the large elevation angle may make it impossible to directly observe areas near the underlying plane, resulting in observation blind spots. In cases where the illumination elevation angle is extremely large, the influence of range variant envelope error and phase modulations becomes more serious, and traditional two-step motion compensation (MOCO) methods may fail to provide accurate imaging. In addition, conventional phase gradient autofocus (PGA) algorithms suffer from reduced performance in scenes with few strong scattering points. To address these practical challenges, we propose an improved phase-weighted estimation PGA algorithm that analyzes the motion error of UAV SAR under a large elevation angle, providing a solution for high-order range variant motion error. Based on this algorithm, we introduce a combined focusing method that applies a threshold value for selection and optimization. Unlike traditional MOCO methods, our proposed method can more accurately compensate for spatially variant motion error in the case of scenes with few strong scattering points, indicating its wider applicability. The effectiveness of our proposed approach is verified by simulation and real data experimental results. [ABSTRACT FROM AUTHOR]

In order to find the causes of statistical line loss abnormalities and propose better loss reduction strategies, it is necessary to improve the accuracy of theoretical line loss calculations. Since Distributed Generation (DG) access to the distribution network causes variability of power flow in the distribution network within a short period, the error of the traditional line loss calculation method increases. For the line loss calculation of medium-voltage distribution networks containing DGs with high-density collection data, a continuous line loss calculation method for the distribution network was proposed, aiming at improving the accuracy compared with the traditional line loss calculation method. The proposed method makes full use of the high-density collection data on the dispatch side and DG side, distributing the supply power to each load node by power to calculate real-time power flow, thus obtaining a more credible line loss value. The effectiveness and accuracy of the proposed method were verified in the IEEE 17-node distribution system. [ABSTRACT FROM AUTHOR]

Data collection is more difficult in distribution network than transmission networks since the structure of distribution networks is more complex. As a result, data could be partly abnormal or missing, which cannot completely describe the operation status of distribution network. In addition, access of distributed generation (DG) to distribution network further aggravates the variability of power flow in distribution network. The traditional deterministic line loss calculation method has some limitations in accurately estimating the line loss of distribution network with DG. A line loss interval calculation method based on power flow calculation and linear optimization is proposed, considering abnormal data collection and distribution network power flow variability. The linear optimization model is established according to sensitivity of line loss to the injected power and sensitivity of transmission power of first branch to the injected power. Introducing the scheduling information into the optimization model, a reliable line loss fluctuation interval can be obtained which actual line loss locates. The effectiveness of the proposed algorithm is verified in IEEE 33-bus distribution network system. [ABSTRACT FROM AUTHOR]

Large-scale multispectral remote sensing data are often unavailable for some practical applications. Spectral resolution enhancement for large-scale multispectral remote sensing images by incorporating small-scale hyperspectral remote sensing images is an alternative way to generate remote sensing images with both large spatial range and high spectral resolution. This paper proposes an improved spectral resolution enhancement method (ISREM) using spectral matrix and weighting the spectral angle of the transformation matrix. ISREM is tested in a typical area of the Three-River Headwaters region (TRHR) to produce a synthetic hyperspectral image (HSI). Two existing spectral resolution enhancement methods, the color resolution improvement software package (CRISP) and spectral resolution enhancement method (SREM), are adopted to compare with ISREM. To further test the practicality of the synthetic HSIs generated by the ISREM, CRISP and SREM, they are used to estimate the coverage of native plant species (NPS) using support vector machines (SVM) and random forest (RF) regressions. The experimental results are as follows. (1) For the Pearson correlation coefficient between the synthetic HSI and original image, ISREM yielded the largest value of 0.9582, followed by CRISP and SREM with values of 0.9480 and 0.9514. For spectral similarity, the HSI generated by the ISREM was the closest to the original reference HSI in the spectral curve. It also showed the best cumulative performance with the use of the three quality evaluation indexes. (2) The identification accuracies of native plant species were 93.51%, 90.91%, 89.61% and 89.61% using generated HSIs and original multispectral image (MSI) within a threshold of 20%, respectively. Compared with original MSI, the synthetic HSI showed better ability to identify NPS in the study area, which further illustrated the effectiveness of the ISREM. (3) The ISREM can reduce the strict requirement of pure pixels and maintain the quality of synthetic HSI by spectral angle weighting. Hence, the proposed ISREM outperforms the existing CRISP and SREM methods in image spectral resolution enhancement of multispectral remote sensing images. [ABSTRACT FROM AUTHOR]

With the widespread attention on clean energy use and energy efficiency, the integrated energy system (IES) has received considerable research and development. This paper proposed an electricity-gas IES optimization planning model based on a coupled combined cooling heating and power system (CCHP). The planning and operation of power lines and gas pipelines are considered. Regarding CCHP as the coupled hub of an electricity-gas system, the proposed model minimizes total cost in IES, with multistage planning and multi-scene analyzing. Renewable energy generation is also considered, including wind power generation and photovoltaic power generation. The numerical results reveal the replacing and adding schemes of power lines and gas pipelines, the optimal location and capacity of CCHP. In comparison with conventional separation production (SP), the optimization model which regards CCHP as the coupled hub attains better economy. At the same time, the influence of electricity price and natural gas price on the quantities of purchasing electricity and purchasing gas in the CCHP system is analyzed. According to the simulation result, a benchmark gas price is proposed, which shows whether the CCHP system chooses power generation. The model results and discussion demonstrate the validity of the model. [ABSTRACT FROM AUTHOR]

This paper proposes a novel adaptive consensus algorithm (ACA) for distributed heat-electricity energy management (HEEM) of an islanded microgrid. In order to simultaneously satisfy the heat-electricity energy balance constraints, ACA is implemented with a switch between unified consensus and independent consensus according to the dynamic energy mismatches. The feasible operation region of a combined heat and power (CHP) unit is decomposed into eight searching sub-regions, thus its electricity and heat energy outputs can simultaneously match the incremental cost consensus requirement and the heat-electricity energy balance constraints. Case studies are thoroughly carried out to verify the performance of ACA for distributed HEEM of an islanded microgrid. [ABSTRACT FROM AUTHOR]

The extracellular secreted protein of Bifidobacterium longum (B. longum) plays an important role in maintaining the homeostasis of the human intestinal microenvironment. However, the mechanism(s) of interaction remain unclear. Lysozyme is a kind of antibacterial peptide. In this study, the amino acid sequence of a lysozyme-like protein of B. longum based on whole-genome data of an isolate from human gut feces was found. We further predicted functional domains from the amino acid sequence, purified the protein, and verified its bioactivity. The growth of some bacteria were significantly delayed by the 020402_LYZ M1 protein. In addition, the gut microbiota was analyzed via high-throughput sequencing of 16S rRNA genes and an in vitro fermentation model, and the fluctuations in the gut microbiota under the treatment of 020402_LYZ M1 protein were characterized. The 020402_LYZ M1 protein affected the composition of human gut microbiota significantly, implying that the protein is able to communicate with intestinal microbes as a regulatory factor. [ABSTRACT FROM AUTHOR]

Let G be a group. D p (G) = ⋂ H ≤ G N G (H ′ (p)) is defined and, the properties of D p (G) are investigated. It is proved that D p (G) = P [ A ] , where P = D (P) is the Sylow p-subgroup and A = N (A) is a Hall p ′ -subgroup of D p (G) , respectively. Furthermore, it is proved in a group G that (1) D p (G) = 1 if and only if C G (G ′ (p)) = 1 ; (2) O p ′ (D p (G)) ≤ Z ∞ (O p (G)) and (3) if Z (G ′ (p)) = 1 , then C G (G ′ (p)) = D p (G) . [ABSTRACT FROM AUTHOR]

Using data from the Integrated Global Radiosonde Archive Version 2 (IGRA2) and the Multi Model Ensemble (MME) of four global climate models (GCMs), named CanESM5, IPSL-CM6A-LR, MIROC6, and MRI-ESM2-0, within the framework of phase 6 of the Coupled Model Intercomparison Project (CMIP6), we analyzed the changes in atmospheric total column water vapor (TCWV) over Central Asia in the future (2021–2100) under SSP-RCPs scenarios: SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0, and SSP5-8.5, relative to baseline period (1986–2005). Results showed that the annual mean TCWV from IGRA2 was consistent with the model output from 1979 to 2014 in Central Asia. Besides, the spatial distribution of TCWV in Central Asia during the baseline period was consistent between the models. The regional average value of Central Asia was between 10.8 mm and 12.4 mm, and decreased with elevation. TCWV will increase under different SSP-RCPs from 2021 to 2040, but showed different trends after 2040. It will increase under SSP1-1.9 and SSP1-2.6 scenarios from 2021 to 2050, and decrease after that. It will grow from 2021 to 2055 under SSP4-3.4 scenario, and then stay essentially constant. Under SSP2-4.5 and SSP4-6.0 scenarios, TCWV will rise rapidly during 2021–2065, but the growth will decline from 2065 to 2100. TCWV will continue to increase under SSP3-7.0 and SSP5-8.5 scenarios, and the largest increase is projected under SSP5-8.5 scenario. Change in near-surface temperature (Ts) matched the change in TCWV, but changes in precipitation and evapotranspiration are not significant during 2021–2100. In spite of the large variations in TCWV under different SSP-RCPs, the dominant characteristic in all scenarios shows that a large TCWV increase is demonstrated over areas with small TCWV amounts during the baseline period. On the contrary, increases will be small where the TCWV amounts had been large during the baseline period. The change in TCWV is highly correlated to the increase in Ts in Central Asia. Under SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0, and SSP5-8.5 scenarios, the higher the temperature due to higher radiative forcing, the steeper the regression slope between TCWV and Ts change. It is closest to the theoretical value of the Clausius-Clapeyron equation under SSP3-7.0 and SSP5-8.5 scenarios, but not presented under other scenarios. Spatially, steeper regression slopes during 2021–2100 have been found around the Caspian Sea in the southwest and in the high-elevation areas in the southeast of Central Asia, which is likely related to the abundant local water supply for evaporation. [ABSTRACT FROM AUTHOR]

In this study, an existing combination approach that maximizes temporal correlations is used to combine six passive microwave satellite soil moisture products from 1998 to 2015 to assess its added value in long-term applications. Five of the products used are included in existing merging schemes such as the European Space Agency's essential climate variable soil moisture (ECV) program. These include the Special Sensor Microwave Imagers (SSM/I), the Tropical Rainfall Measuring Mission (TRMM/TMI), the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) sensor on the National Aeronautics and Space Administration's (NASA) Aqua satellite, the WindSAT radiometer, onboard the Coriolis satellite and the soil moisture retrievals from the Advanced Microwave Scanning Radiometer 2 (AMSR2) sensor onboard the Global Change Observation Mission on Water (GCOM-W). The sixth, the microwave radiometer imager (MWRI) onboard China's Fengyun-3B (FY3B) satellite, is absent in the ECV scheme. Here, the normalized soil moisture products are merged based on their availability within the study period. Evaluation of the merged product demonstrated that the correlations and unbiased root mean square differences were improved over the whole period. Compared to ECV, the merged product from this scheme performed better over dense and sparsely vegetated regions. Additionally, the trends in the parent inputs are preserved in the merged data. Further analysis of FY3B's contribution to the merging scheme showed that it is as dependable as the widely used AMSR2, as it contributed significantly to the improvements in the merged product. [ABSTRACT FROM AUTHOR]

Very high-resolution remote sensing change detection has always been an important research issue due to the registration error, robustness of the method, and monitoring accuracy, etc. This paper proposes a robust and more accurate approach of change detection (CD), and it is applied on a smaller experimental area, and then extended to a wider range. A feature space, including object features, Visual Geometry Group (VGG) depth features, and texture features, is constructed. The difference image is obtained by considering the contextual information in a radius scalable circular. This is to overcome the registration error caused by the rotation and shift of the instantaneous field of view and also to improve the reliability and robustness of the CD. To enhance the robustness of the U-Net model, the training dataset is constructed manually via various operations, such as blurring the image, increasing noise, and rotating the image. After this, the trained model is used to predict the experimental areas, which achieved 92.3% accuracy. The proposed method is compared with Support Vector Machine (SVM) and Siamese Network, and the check error rate dropped to 7.86%, while the Kappa increased to 0.8254. The results revealed that our method outperforms SVM and Siamese Network. [ABSTRACT FROM AUTHOR]

Many life activities and key functions in organisms are maintained by different types of protein–protein interactions (PPIs). In order to accelerate the discovery of PPIs for different species, many computational methods have been developed. Unfortunately, even though computational methods are constantly evolving, efficient methods for predicting PPIs from protein sequence information have not been found for many years due to limiting factors including both methodology and technology. Inspired by the similarity of biological sequences and languages, developing a biological language processing technology may provide a brand new theoretical perspective and feasible method for the study of biological sequences. In this paper, a pure biological language processing model is proposed for predicting protein–protein interactions only using a protein sequence. The model was constructed based on a feature representation method for biological sequences called bio-to-vector (Bio2Vec) and a convolution neural network (CNN). The Bio2Vec obtains protein sequence features by using a "bio-word" segmentation system and a word representation model used for learning the distributed representation for each "bio-word". The Bio2Vec supplies a frame that allows researchers to consider the context information and implicit semantic information of a bio sequence. A remarkable improvement in PPIs prediction performance has been observed by using the proposed model compared with state-of-the-art methods. The presentation of this approach marks the start of "bio language processing technology," which could cause a technological revolution and could be applied to improve the quality of predictions in other problems. [ABSTRACT FROM AUTHOR]

The strawberry vein banding virus (SVBV) open reading frame (ORF) VI encodes a P6 protein known as the RNA silencing suppressor. This protein is known to form inclusion like granules of various sizes and accumulate in both the nuclei and the cytoplasm of SVBV-infected plant cells. In this study, we have determined that the P6 protein is the only trans-activator (TAV) encoded by SVBV, and can efficiently trans-activate the translation of downstream gfp mRNA in a bicistron derived from the SVBV. Furthermore, the P6 protein can trans-activate the expression of different bicistrons expressed by different caulimovirus promoters. The P6 protein encoded by SVBV from an infectious clone can also trans-activate the expression of bicistron. Through protein-protein interaction assays, we determined that the P6 protein could interact with the cell translation initiation factor FveIF3g of Fragaria vesca and co-localize with it in the nuclei of Nicotiana benthamiana cells. This interaction reduced the formation of P6 granules in cells and its trans-activation activity on translation. [ABSTRACT FROM AUTHOR]